AI proves instrumental in predicting antidepressant efficacy, Dutch study suggests

Antidepressants are commonly used in treating moderate to severe depression. Regrettably, patients and healthcare workers must endure a waiting period of six to eight weeks to gauge any signs of improvement. If no progress is observed, only then is the treatment adjusted. However, scientists from the Amsterdam University Medical Center (Amsterdam UMC) and the Radboud University Medical Center in the Netherlands have discovered a way to shorten the waiting time using artificial intelligence.

The focus of the scientists was on sertraline, one of the most frequently prescribed initial treatment options for depression. Notwithstanding, it typically benefits only half the patients. The patient's condition and the effects of the drug can only be assessed after waiting for a few weeks.

These cycles, as we refer to them, can potentially last up to six months – Maarten Poirot, a PhD student at Amsterdam UMC and the lead author of the study, informed Euronews.

The team led by Poirot amassed various data, which comprised predictive MRI factors like hippocampus volume, blood flow rates, and clinical information. They devised an algorithm based on these data. They concluded that the amalgamation of all this information could lead to establishing a model capable of predicting treatment outcomes.

According to the World Health Organization (WHO), approximately 280 million people around the globe suffer from depression - accounting for about 3.8% of the world's population. The disorder afflicts 5.0% of adults and 5.7% of individuals aged 60 and above. Furthermore, it is becoming increasingly prevalent among children and teenagers. Effectiveness and timely initiation of treatment are crucial. The longer the delay in seeing results, the lesser the odds of successfully treating someone suffering from depression.